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Article
Publication date: 29 June 2021

Asgar Ali and K.N. Badhani

The study investigates the impact of higher moments on cross-sectional returns in the Indian equity market.

Abstract

Purpose

The study investigates the impact of higher moments on cross-sectional returns in the Indian equity market.

Design/methodology/approach

Using the daily data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019, the study evaluates the relationship between higher moments (skewness and kurtosis) and stock returns at individual stock and portfolio levels. The variations in the returns of the equal-weighted and the value-weighted portfolios are analysed, where the portfolios are constructed by sorting the stocks on skewness and kurtosis. The returns are adjusted for five common factors – market excess-returns, size, value, momentum and illiquidity, to controls other cross-sectional effects. Besides, the study employs Fama-MacBeth cross-sectional regression and time-series tests of higher moments as robustness measures.

Findings

The study presents higher moments anomaly in the Indian equity market. Contrary to what is expected based on a risk-averse rational agent model, a robust positive relationship is observed between the skewness and stock returns. The relationship between the kurtosis and stock returns is negative, albeit statistically weak. These results are robust for the Fama-MacBeth cross-sectional regression and time-series tests.

Originality/value

It is among the earlier attempts to investigate the pricing impact of higher moments at different levels of asset prices in an emerging market. Besides the standard portfolio methodology for explaining cross-sectional variations, the study also employs the time-series tests for higher moment factors, hence provides more robust results. Results have wider implications for asset pricing in emerging markets and highlight many issues for further research.

Details

Managerial Finance, vol. 47 no. 12
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 29 March 2021

Xiaoyue Chen, Bin Li and Andrew C. Worthington

The purpose of this paper is to examine the relationships between the higher moments of returns (realized skewness and kurtosis) and subsequent returns at the industry…

Abstract

Purpose

The purpose of this paper is to examine the relationships between the higher moments of returns (realized skewness and kurtosis) and subsequent returns at the industry level, with a focus on both empirical predictability and practical application via trading strategies.

Design/methodology/approach

Daily returns for 48 US industries over the period 1970–2019 from Kenneth French’s data library are used to calculate the higher moments and to construct short- and medium-term single-sort trading strategies. The analysis adjusts returns for common risk factors (market, size, value, investment, profitability and illiquidity) to confirm whether conventional asset pricing models can capture these relationships.

Findings

Past skewness positively relates to subsequent industry returns and this relationship is unexplained by common risk factors. There is also a time-varying effect in which the predictive role of skewness is much stronger over business cycle expansions than recessions, a result consistent with varying investor optimism. However, there is no significant relationship between kurtosis and subsequent industry returns. The analysis confirms robustness using both value- and equal-weighted returns.

Research limitations/implications

The calculation of realized moments conventionally uses high-frequency intra-day data, regrettably unavailable for industries. In addition, the chosen portfolio-sorting method may omit some information, as it compares only average group returns. Nonetheless, the close relationship between skewness and future returns at the industry level suggests variations in returns unexplained by common risk factors. This enriches knowledge of market anomalies and questions yet again weak-form market efficiency and the validity of conventional asset pricing models. One suggestion is that it is possible to significantly improve the existing multi-factor asset pricing models by including industry skewness as a risk factor.

Practical implications

Given the relationship between skewness and future returns at the industry level, investors may predict subsequent industry returns to select better-performing funds. They may even construct trading strategies based on return distributions that would generate abnormal returns. Further, as the evaluation of individual stocks also contains industry information, and stocks in industries with better performance earn higher returns, risks related to industry return distributions can also shed light on individual stock picking.

Originality/value

While there is abundant evidence of the relationships between higher moments and future returns at the firm level, there is little at the industry level. Further, by testing whether there is time variation in the relationship between industry higher moments and future returns, the paper yields novel evidence concerning the asymmetric effect of stock return predictability over business cycles. Finally, the analysis supplements firm-level results focusing only on the decomposed components of higher moments.

Details

Review of Accounting and Finance, vol. 20 no. 1
Type: Research Article
ISSN: 1475-7702

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Article
Publication date: 7 September 2020

Tianning Ma, Shuo Li and Xu Feng

This paper studies whether individual stocks provide higher returns than government bond in the Chinese market.

Abstract

Purpose

This paper studies whether individual stocks provide higher returns than government bond in the Chinese market.

Design/methodology/approach

The authors compare individual stock returns and government bond returns in the Chinese market.

Findings

The authors find that more than half of individual stocks underperform government bonds over the same period in China, which highlights the important role of positive skewness in the distribution of individual stock returns. The high return of a few stocks is the reason why the stock market return is higher than that of government bond in China.

Originality/value

The results of this paper emphasize that portfolio diversification plays an important role in the Chinese market.

Details

China Finance Review International, vol. 11 no. 2
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 13 March 2009

Matthew Hood, John R. Nofsinger and Kenneth Small

The purpose of this paper is to introduce a non‐normality premium (NNP) to identify the extra return that will compensate an investor for a non‐normal return distribution…

Abstract

Purpose

The purpose of this paper is to introduce a non‐normality premium (NNP) to identify the extra return that will compensate an investor for a non‐normal return distribution. The NNP quantifies the economic significance of non‐normality to complement a statistical significance test of non‐normality, such as the Jarque‐Bera test.

Design/methodology/approach

The NNP is patterned after the risk premium, the amount that compensates an investor for the risk of an investment. The theoretical NNP is examined on the margins with Taylor series approximation and applied to hedge fund data.

Findings

An increase of 1 in the skewness has the same effect on an investor as an increase in the mean of 2.5 basis points per month. An increase of 1 in the kurtosis has the same effect on an investor as a decrease in the mean of 0.15 basis points per month. A sample of 716 hedge funds revealed that while 72 per cent statistically reject normality, only 29 per cent require more than a single basis point per month difference in the mean to compenscate an investor for the non‐normality.

Originality/value

The NNP allows for a valuation on the higher moments (skewness and kurtosis) of an investor's return distribution. The evaluation is tailored to the individual through use of a utility function. Once applied to an alternative investment vehicle, it is learned that rejecting normality is not sufficient grounds to suspect that the non‐normality is important to investors.

Details

Managerial Finance, vol. 35 no. 4
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 20 March 2018

Yaojie Zhang, Yu Wei and Benshan Shi

The purpose of this paper is to develop a loan insurance pricing model allowing for the skewness and kurtosis existing in underlying asset returns.

Abstract

Purpose

The purpose of this paper is to develop a loan insurance pricing model allowing for the skewness and kurtosis existing in underlying asset returns.

Design/methodology/approach

Using the theory of Gram-Charlier option, the authors first derive a closed-form solution of the Gram-Charlier pricing model. To address the difficulties in implementing the pricing model, the authors subsequently propose an iterative method to estimate skewness and kurtosis in practical application, which shows a relatively fast convergence rate in the empirical test.

Findings

Not only the theoretical analysis but also the empirical evidence shows that the effects of skewness and kurtosis on loan insurance premium tend to be negative and positive, respectively. Furthermore, the actual values of skewness and kurtosis are usually negative and positive, respectively, which leads to the empirical result that the pricing model ignoring skewness and kurtosis substantially underestimates loan insurance premium.

Originality/value

This paper proposes a loan insurance pricing model considering the skewness and kurtosis of asset returns, in which the authors use the theory of Gram-Charlier option. More importantly, the authors further propose a novel iterative method to estimate skewness and kurtosis in practical application. The empirical evidence suggests that the Gram-Charlier pricing model captures the information content of skewness and kurtosis.

Details

China Finance Review International, vol. 8 no. 4
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 27 June 2018

Xia He, Wenling Liao, Guorong Wang, Lin Zhong and Mengyuan Li

The purpose of this study is to investigate the influence of texture on hydrodynamic lubrication performance of slide surface from the perspective of skewness and kurtosis.

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Abstract

Purpose

The purpose of this study is to investigate the influence of texture on hydrodynamic lubrication performance of slide surface from the perspective of skewness and kurtosis.

Design/methodology/approach

Hydrodynamic lubrication theoretical model of textured surface was established based on two-dimensional Reynolds equation, and finite difference algorithm was used as the numerical approach in the paper. Skewness and kurtosis of surface were obtained by discrete calculation.

Findings

Numerical analysis results show that the influence law of texture types on skewness, kurtosis and hydrodynamic lubrication was the more negative skewness and higher kurtosis, the better hydrodynamic lubrication performance when texture cross section contour and geometric parameters were the same. Similarly, the same influence law of skewness, kurtosis and hydrodynamic lubrication performance by texture cross-section contour was observed. However, it was unable to evaluate the effect of texture angle on hydrodynamic lubrication performance of textured surface from the perspective of skewness and kurtosis.

Originality/value

This paper confirms the feasibility of evaluating influence of texture types and texture cross-section contour on hydrodynamic lubrication performance from the perspective of skewness and kurtosis and provides a way to optimize texture type and texture cross section.

Details

Industrial Lubrication and Tribology, vol. 70 no. 5
Type: Research Article
ISSN: 0036-8792

Keywords

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Article
Publication date: 31 May 2008

Sol Kim

For the KOSPI 200 index options market. we examine the power of influence on pricing options of the skewness and the kurtosis of the risk neutral distribution. We compare…

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3

Abstract

For the KOSPI 200 index options market. we examine the power of influence on pricing options of the skewness and the kurtosis of the risk neutral distribution. We compare the Black and Scholes (1973) model which does not consider the skewness or the kurtosis of the risk neutral distribution with Corrado and sue 1996)’s model which consider both the skewness and the kurtosis and the models which consider only the skewness or the kurtosis.

It is found that Corrado and sue 1996)‘s model which consider both skewness and kurtosis shows the best performance closely followed by the model which consider only the skewness for tile in-sample pricing and the out-of-sample pricing. As a result. it contributes to pricing options to consider both skewness and kurtosis and the skewness is more important factor for pricing options than the kurtosis.

Details

Journal of Derivatives and Quantitative Studies, vol. 16 no. 1
Type: Research Article
ISSN: 2713-6647

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Article
Publication date: 28 September 2010

Martin Eling, Simone Farinelli, Damiano Rossello and Luisa Tibiletti

Recent literature discusses the persistence of skewness and tail risk in hedge fund returns. The aim of this paper is to suggest an alternative skewness measure…

Abstract

Purpose

Recent literature discusses the persistence of skewness and tail risk in hedge fund returns. The aim of this paper is to suggest an alternative skewness measure, Azzalini's skewness parameter delta, which is derived as the normalized shape parameter from the skew‐normal distribution. The paper seeks to analyze the characteristics of this skewness measure compared with other indicators of skewness and to employ it in some typical risk and performance measurements.

Design/methodology/approach

The paper first provides an overview of the skew‐normal distribution and its mathematical formulation. Then it presents some empirical estimations of the skew‐normal distribution for hedge fund returns and discusses the characteristics of using delta with respect to classical skewness coefficients. Finally, it illustrates how delta can be used in risk management and in a performance measurement context.

Findings

The results highlight the advantages of Azzalini's skewness parameter delta, especially with regard to its interpretation. Delta has a limpid financial interpretation as a skewness shock on normally distributed returns. The paper also derives some important characteristics of delta, including that it is more stable than other measures of skewness and inversely related to popular risk measures such as the value‐at‐risk (VaR) and the conditional value‐at‐risk (CVaR).

Originality/value

The contribution of the paper is to apply the skew‐normal distribution to a large sample of hedge fund returns. It also illustrates that using Azzalini's skewness parameter delta as a skewness measure has some advantages over classical skewness coefficients. The use of the skew‐normal and related distributions is a relatively new, but growing, field in finance and not much has been published on the topic. Skewness itself, however, has been the subject of a great deal of research. Therefore, the results contribute to three fields of research: skewed distributions, risk measurement, and hedge fund performance.

Details

International Journal of Managerial Finance, vol. 6 no. 4
Type: Research Article
ISSN: 1743-9132

Keywords

Content available
Article
Publication date: 4 August 2020

Kanak Meena, Devendra K. Tayal, Oscar Castillo and Amita Jain

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness

Abstract

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness, the uneven distribution of attributes occurs, and it can cause a severe load imbalance problem. When database join operations are applied to these datasets, skewness occurs exponentially. All the algorithms developed to date for the implementation of database joins are highly skew sensitive. This paper presents a new approach for handling data-skewness in a character- based string similarity join using the MapReduce framework. In the literature, no such work exists to handle data skewness in character-based string similarity join, although work for set based string similarity joins exists. Proposed work has been divided into three stages, and every stage is further divided into mapper and reducer phases, which are dedicated to a specific task. The first stage is dedicated to finding the length of strings from a dataset. For valid candidate pair generation, MR-Pass Join framework has been suggested in the second stage. MRFA concepts are incorporated for string similarity join, which is named as “MRFA-SSJ” (MapReduce Frequency Adaptive – String Similarity Join) in the third stage which is further divided into four MapReduce phases. Hence, MRFA-SSJ has been proposed to handle skewness in the string similarity join. The experiments have been implemented on three different datasets namely: DBLP, Query log and a real dataset of IP addresses & Cookies by deploying Hadoop framework. The proposed algorithm has been compared with three known algorithms and it has been noticed that all these algorithms fail when data is highly skewed, whereas our proposed method handles highly skewed data without any problem. A set-up of the 15-node cluster has been used in this experiment, and we are following the Zipf distribution law for the analysis of skewness factor. Also, a comparison among existing and proposed techniques has been shown. Existing techniques survived till Zipf factor 0.5 whereas the proposed algorithm survives up to Zipf factor 1. Hence the proposed algorithm is skew insensitive and ensures scalability with a reasonable query processing time for string similarity database join. It also ensures the even distribution of attributes.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

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Article
Publication date: 11 November 2014

Ahmed F. Siddiqi

The purpose of this paper is to discuss how numerous tests that are available in statistical literature to assess normality of a given set of observations perform in…

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1121

Abstract

Purpose

The purpose of this paper is to discuss how numerous tests that are available in statistical literature to assess normality of a given set of observations perform in normal and near-normal situations. Not all these tests are suitable for all situations but each test has an exclusive area of application.

Design/methodology/approach

These tests are assessed for their power at varying degrees of skewness, kurtosis and sample size on the basis of simulated experiments.

Findings

It is observed that almost all these tests are indifferent for smaller values of skewness and kurtosis. Further, the power of accepting normality reduces with increasing sample size.

Originality/value

The article gives guidelines to researchers to apply normality assessing tests in different situations.

Details

Journal of Modelling in Management, vol. 9 no. 3
Type: Research Article
ISSN: 1746-5664

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